شكل هذه المشكلة
Too much arrives to check it all, so you sample
المشكلة
Call-center teams needed searchable Arabic transcripts across dialects. Recorded calls that cannot be searched are closer to a liability than an asset - they must be retained and produced on request, but nothing can be learned from them. Arabic sharpens the problem: callers speak in dialect while most systems are built for Modern Standard Arabic, so accuracy varies with who happens to be calling, which is the worst possible property for a compliance record.
ما بنيناه
We delivered speech-to-text processing that converted conversations into structured text suitable for search and downstream analysis.
ما تغيّر
| المقياس | قبل | بعد |
|---|---|---|
| Word error rate on Gulf-dialect calls | 31% | 12.7% |
| Spread between best- and worst-performing dialect groups | 19 points | 5 |
| Call archive searchable | لا قياس سابق | all of it, previously none |
Word error rate on Gulf-dialect calls
Spread between best- and worst-performing dialect groups
الأرقام من سجلات التنفيذ الخاصة بالممارسة للمشروع المذكور، مقيسةً مقابل العملية التي سبقته.
ما توقّف عليه
Handling dialect variation is what turned the archive from stored audio into a queryable record - uneven accuracy across callers would have made any aggregate drawn from it misleading. Relevant to any regulated operation retaining Arabic voice records it currently cannot read.
- خط الخدمة
- Service & Conversation AI
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